Data Science Lead (CV + ML)

Posted Yesterday
Be an Early Applicant
3 Locations
Hybrid
Senior level
Healthtech
The Role
Develop, validate, and deploy computer vision and machine learning algorithms for clinical decision support using imaging and sensor data. Own projects from messy data and modeling through rigorous evaluation and production integration. Collaborate with hardware, software, medical, and clinical research teams, apply classical and deep learning methods, support regulatory readiness, deliver production-quality Python code, and mentor colleagues.
Summary Generated by Built In
Mission

Neko is redefining what prevention means, from treating illness when it arrives, to sustaining health before it's ever at risk. Our mission: make data-driven, preventative care accessible to more people, before symptoms appear.
In a single, non-invasive visit under an hour, proprietary technology and direct clinical care combine to deliver personalised, actionable insights. It's a team that thinks in 10x, not 10%. Every role here plays a part in building a world where prevention is the norm, and where your work genuinely helps people live longer, healthier lives.

Role Purpose

Neko’s body scan captures rich imaging data across the human body. Turning it into validated, production-ready algorithms with real clinical impact is the job. We are hiring Senior Data Scientists to work across computer vision problems such as skin imaging, tissue imaging and body measurement [TBC: confirm active project areas].

You will collaborate with hardware engineers, software engineers, clinical scientists and other data scientists to develop prototypes, validate clinical use cases, and deliver algorithms and ML models into production, integrated into Neko Health’s clinics and products.

We are looking for a broad computer vision background: people who are as comfortable with geometry, 3D and classical image processing as with modern deep learning, and who know which to reach for.

 
What You’ll Deliver in the First 6–12 Months
  • Develop, verify, validate and deploy computer vision and ML algorithms for clinical decision support, and contribute to new product features or research breakthroughs that improve member outcomes (Member-first, always).

  • Own problems end to end, from a vague question and messy real-world data, through modelling and evaluation, to a model running in production, across problem areas as priorities evolve (Chase 10X, not 10%).

  • Work with hardware engineers, software engineers, medical doctors and clinical researchers to close the gap between what the sensors capture and what runs in the clinic (Tech-enabled, human-centred).

  • Combine classical, geometric and learned methods, using semi-, self- or weakly-supervised approaches where expert labels are scarce, and evaluate them rigorously. Analyse clinical study data and support regulatory readiness (Optimistic truth seeking).

  • Deliver production-quality code and integrate it into Neko's backend infrastructure, using AI tools to move faster while keeping the judgment and ownership your own.

  • Share what you know. Mentor colleagues, review code and designs, and help build a culture of openness and continuous improvement

 
Requirements
 
  • Extensive experience in modern computer vision and deep learning on real-world camera or sensor data, such as detection, segmentation, tracking or 3D perception, with the judgment to know when a classical or geometric method is the better tool.

  • A track record of making algorithms work under messy, real-world capture conditions, such as lighting, motion, optics and calibration, and shipping them to production.

  • Strong machine learning fundamentals and algorithmic thinking, with breadth beyond one niche. You pick up a new problem type quickly and know how to evaluate it properly.

  • Strong software engineering skills in Python, with production-level code, testing and code review.

  • 5+ years of relevant industry experience, or 2+ years post-PhD.

  • Experience working in cross-functional R&D teams alongside hardware and software engineers.

  • Clear communication. You can explain a trade-off to a clinician, an engineer and a manager.

  • AI Fluent - confident in using latest tooling developments to increase productivity and efficiency

  • MSc or PhD in Computer Vision, Machine Learning, Computer Science, Physics, Engineering or a related field.

  • Motivated to apply strong science to improve preventative healthcare.

 
Preferred
  • Experience with multi-view geometry or matching across views and time, such as tracking, registration, calibration, SLAM or re-identification.

  • Experience with 3D vision or reconstruction.

  • Experience with label-efficient learning (semi-supervised, self-supervised, pseudo-labelling) and large-scale data pipelines.

  • Experience with sensor fusion, state estimation or filtering, or with non-RGB imaging such as thermal.

  • Experience teaching or mentoring engineers or researchers in high-growth, mission-driven organisations.

  • Exposure to safety-critical or regulated settings. We'll teach you the rest.

Skills Required

  • Extensive experience in modern computer vision and deep learning using real-world camera or sensor data
  • Experience with detection, segmentation, tracking, or 3D perception
  • Experience developing algorithms for messy real-world capture conditions and shipping them to production
  • Strong machine learning fundamentals and algorithmic thinking
  • Strong Python software engineering skills, including production code, testing, and code review
  • 5+ years of relevant industry experience, or 2+ years post-PhD
  • Experience working in cross-functional R&D teams with hardware and software engineers
  • Clear communication with clinicians, engineers, and managers
  • Confidence using current AI tooling developments to improve productivity and efficiency
  • MSc or PhD in Computer Vision, Machine Learning, Computer Science, Physics, Engineering, or a related field
  • Motivation to apply science to preventative healthcare
  • Experience with multi-view geometry or matching across views and time, including tracking, registration, calibration, SLAM, or re-identification
  • Experience with 3D vision or reconstruction
  • Experience with label-efficient learning and large-scale data pipelines
  • Experience with sensor fusion, state estimation, filtering, or non-RGB imaging such as thermal imaging
  • Experience teaching or mentoring engineers or researchers
  • Exposure to safety-critical or regulated settings

Neko Health Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Neko Health and has not been reviewed or approved by Neko Health.

  • Healthcare Strength — Benefits materials and U.S. role listings describe comprehensive medical, dental, and vision coverage, often including mental-health support for clinical staff. This indicates a strong health-focused foundation aligned with a preventive-care mission.
  • Wellbeing & Lifestyle Benefits — Offerings include a complimentary annual Neko Health scan for employees (often extended to eligible family members), a monthly wellness allowance, and wellness rewards. These distinctive perks emphasize preventive health and everyday wellbeing.
  • Leave & Time Off Breadth — Paid time off and paid holidays are standard, with flexible time policies depending on role. Clinician postings also call out CME days in some markets.

Neko Health Insights

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The Company
HQ: Stockholm
126 Employees
Year Founded: 2018

What We Do

Neko Health is a Swedish health-tech company co-founded in 2018 by Hjalmar Nilsonne and Daniel Ek. Neko's vision is to create a healthcare system that can help people stay healthy through preventive measures and early detection. This requires completely reimagining the patient's experience and incorporating the latest advances in sensors and AI. Neko has developed a new medical scanning technology concept to make it possible to do broad and non-invasive health data collection that is convenient and affordable for the public.

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